Availability Modeling and Analyzing of Multi-state Control Unit under Condition-based Maintenance

doi:10.3969/j.issn.1000-1093.2017.11.022

Abstract

Abstract: A modeling method of control units under condition-based maintenance (CBM) based on multi-state dynamic Bayesian network (DBN)is proposed for describing the dynamic characteristics of system. After defining multi-state components, a state-transition model based on Markov model is established in considering CBM, and absorbing state is introduced. A multi-state DBN model is established to determine the state-transition relationships with non-repair, perfect repair, imperfect repair, CBM and absorbing state. And the conditional probability value is obtained according to the logic relationship of series system and parallel system. A control unit is taken for example. The dynamic fault tree (DFT) and DBN model are established to determine the reliability curves of control unit and its components under different repair modes. And the weak links of reliability design are found through importance analysis. The simulated results show that the control unit under CBM has higher availability than the perfectly and imperfectly repaired control units. The availability of repairable components with degradation states can be predicted, and a maintenance policy can be made accordingly. Key

Key words: ordnancescienceandtechnology, dynamicBayesiannetwork, conditional-basedmaintenance, perfectrepair, imperfectrepair, dynamicfaulttree, importanceanalysis

CLC Number:

LI Zhi-qiang, XU Ting-xue, GU Jun-yuan, AN Jin, DONG Qi. Availability Modeling and Analyzing of Multi-state Control Unit under Condition-based Maintenance[J]. Acta Armamentarii, 2017, 38(11): 2240-2250.

References

［1］ Langseth H, Portinale L. Bayesian networks in reliability[J]. Reliability Engineering & System Safety, 2007, 92(1):92-108.
[2］ Mahadevan S, Zhang R, Smith N. Bayesian networks for system reliability reassessment[J]. Structural Safety, 2001, 23(3):231-251.
[3］ Lisnianski A, Frenkel I, Ding Y. Multi-state system reliability analysis and optimization for engineers and industrial managers[M]. New York, NY, US: Springer, 2010: 29-66.
[4］ Wilson A G, Huzurbazar A V. Bayesian networks for multilevel system reliability[J]. Reliability Engineering & System Safety, 2007, 92(10):1413-1420.
[5］ Codetta-Raiteri D, Bobbio A, Montani S, et al. A dynamic Bayesian network based framework to evaluate cascading effects in a power grid[J]. Engineering Applications of Artificial Intelligence, 2012, 25(4): 683-697.
[6］ Barua S, Gao X D, Pasman H, et al. Bayesian network based dynamic operational risk assessment[J]. Journal of Loss Prevention in the Process Industries, 2016, 41:399-410.
[7］ Zhang L M, Wu X G, Skibniewski M J, et al. Bayesian-network-based safety risk analysis in construction projects[J]. Reliability Engineering & System Safety, 2014, 131(3):29-39.
[8］周忠宝，周经伦，孙权，等. 基于离散时间贝叶斯网络的动态故障树分析方法[J]. 西安交通大学学报, 2007, 41(6): 732-736.
ZHOU Zhong-bao, ZHOU Jing-lun, SUN Quan, et al. Dynamic fault tree analysis method based on discrete time Bayesian networks[J]. Journal of Xi'an Jiaotong University, 2007, 41(6): 732-736. (in Chinese)
[9］周忠宝，马超群，周经伦，等. 基于动态贝叶斯网络的动态故障树分析[J]. 系统工程理论与实践, 2008, 28(2): 35-42.
ZHOU Zhong-bao, MA Chao-qun, ZHOU Jing-lun, et al. Dynamic fault tree analysis based on dynamic Bayesian networks[J]. Systems Engineering—Theory & Practice, 2008, 28(2): 35-42. (in Chinese)

[10］于春雨，郭建英，苑惠娟，等. 指数故障/维修背景下串联系统可用度置信限[J]. 仪器仪表学报, 2016, 37(5): 1079-1086.
YU Chun-yu, GUO Jian-ying, YUAN Hui-juan, et al. Confidence limit of series system availability in exponential fault time and repair-time context[J]. Chinese Journal of Scientific Instrument, 2016, 37(5): 1079-1086. (in Chinese)
[11］刘航，李群湛，郭锴. 基于Markov过程的组合式同相供电装置维修决策优化[J]. 西南交通大学学报, 2017, 52(2): 1-8.
LIU Hang, LI Qun-zhan, GUO Kai. Research on combined co-phase power supply equipment maintenance decision modeling and optimization based on Markov process[J]. Journal of Southwest Jiaotong University, 2017, 52(2): 1-8.(in Chinese)
[12］耿岩，郭霖瀚，王寄明，等. 考虑休眠的两部件系统可用度马氏建模方法[J]. 仪器仪表学报, 2016, 37(9): 1996-2003.
GENG Yan, GUO Lin-han, WANG Ji-ming, et al. Markov modeling method for availability of two-item system under passivation[J]. Chinese Journal of Scientific Instrument, 2016, 37(9): 1996-2003. (in Chinese)
[13］王少华，张耀辉，徐隆洋，等. 基于仿真的多部件系统状态维修决策优化方法[J]. 兵工学报, 2017, 38(3): 568-575.
WANG Shao-hua, ZHANG Yao-hui, XU Long-yang, et al. Optimal condition-based maintenance decision-making method of multi-component system based on simulation[J]. Acta Armamentarii, 2017, 38(3): 568-575.(in Chinese)
[14］樊冬明，任羿，刘林林，等. 基于动态贝叶斯网络的可修GO法模型算法[J]. 北京航空航天大学学报, 2015, 41(11): 2166-2176.
FAN Dong-ming, REN Yi, LIU Lin-lin, et al. Algorithm based-on dynamic Bayesian networks for repairable GO methodology model［J］．Journal of Beijing University of Aeronautics and Astronautics, 2015, 41(11): 2166-2176. (in Chinese)
[15］ Liu Z K, Liu Y H, Cai B P, et al. Dynamic Bayesian network modeling of reliability of subsea blowout preventer stack in presence of common cause failures[J]. Journal of Loss Prevention in the Process Industries, 2015, 38:58-66.
[16］ Cai B P, Liu Y H, Zhang Y W, et al. Dynamic Bayesian networks based performance evaluation of subsea blowout preventers in presence of imperfect repair[J]. Expert Systems with Applications, 2013, 40(18):7544-7554.
[17］朱正福，李长福，何恩山，等. 基于马尔可夫链的动态故障树分析方法[J]. 兵工学报, 2008, 29(9): 1104-1107.
ZHU Zheng-fu, LI Chang-fu, HE En-shan, et al. The dynamic fault tree analysis method based on Markov chain[J]. Acta Armamentarii, 2008, 29(9): 1104-1107. (in Chinese)
[18］ Fort A, Mugnaini M, Vignoli V. Hidden Markov models approach used for life parameters estimations[J]. Reliability Engineering & System Safety, 2015, 136:85-91.
[19］王开铭，赵峰，曹茜. 基于动态贝叶斯网络的高速铁路牵引变电所可靠性分析[J]. 中国安全生产科学技术, 2016, 12(6): 128-135.
WANG Kai-ming, ZHAO Feng, CAO Qian. Reliability analysis on traction substation of high-speed railway based on dynamic Bayesian network[J]. Journal of Safety Science and Technology, 2016, 12(6): 128-135. (in Chinese)
[20］高晓光，陈海洋，符小卫，等. 离散动态贝叶斯网络推理及其应用[M]. 北京: 国防工业出版社, 2016: 44-46.
GAO Xiao-guang, CHEN Hai-yang, FU Xiao-wei, et al. Discrete dynamic Bayesian network inference and its application[M]. Beijing: National Defense Industry Press, 2016: 44-46. (in Chinese)
[21］丛林虎，徐廷学，董琪，等. 基于改进证据理论的导弹状态评估方法[J]. 系统工程与电子技术, 2016, 38(1): 70-76.
CONG Lin-hu, XU Ting-xue, DONG Qi, et al. Missile condition assessment method based on improved evidence theory[J]. System Engineering and Electronics, 2016, 38(1): 70-76. (in Chinese)
[22］王亮，吕卫民，滕克难. 基于测试数据的长期贮存装备实时健康状态评估[J]. 系统工程与电子技术, 2013, 35(6): 1212-1217.
WANG Liang, LYU Wei-min, TENG Ke-nan. Real-time health condition assessment of long-term storage equipment based on testing data[J]. Systems Engineering and Electronics, 2013, 35(6): 1212-1217. (in Chinese)
[23］ Zhang R J, Zhang L L, Dong M X. Multi-state system importance analysis method of fuzzy Bayesian networks[J]. International Journal of Industrial & Systems Engineering, 2015, 21(3): 395-414.
[24］ Ramirez-Marquez J E, Coit D W. Multi-state component criticality analysis for reliability improvement in multi-state systems[J]. Reliability Engineering & System Safety, 2007, 92(12):1608-1619.

第38卷
第11期2017 年11月兵工学报ACTA
ARMAMENTARIIVol.38No.11Nov.2017

[1]	LI Shurui， DUAN Zhuoping， ZHENG Baohui， LUO Guan， HUANG Fenglei. Cylinder Test and Equation of State for DNAN-based Aluminized Melt-cast Explosive [J]. Acta Armamentarii, 2021, 42(7): 1424-1430.
[2]	LOU Wei-peng, ZHENG Chang-song, LI He-yan, CHEN Jian-wen, ZHANG Zhou-li, MA Yuan. Research on Critical Open and Close Pressures of an Oil Discharge Valve for High Speed Wet Shifting Clutch [J]. Acta Armamentarii, 2017, 38(9): 1665-1672.
[3]	WANG Xian-cheng, YANG Shao-qing, MA Ning, ZHAO Wen-zhu. Research on Wear Model for Cylinder Liners in Vehicle Diesel Engines under Dynamic Load [J]. Acta Armamentarii, 2017, 38(9): 1673-1680.
[4]	SUN Hao-ze, CHANG Tian-qing, WANG Quan-dong, KONG De-peng, DAI Wen-jun. Image Detection Method for Tank and Armored Targets Based on Hierarchical Multi-scale Convolution Feature Extraction [J]. Acta Armamentarii, 2017, 38(9): 1681-1691.
[5]	ZHANG Yu-yan, SUN Sha-sha, WANG Zhen-chun, CAO Hai-yao, ZHAN Zai-ji. Simulation and Measurement of Surface Transient Temperature Field of High-speed Current-carrying Armature [J]. Acta Armamentarii, 2017, 38(9): 1692-1698.
[6]	LI Chen-ming， HUAN Chao， SHI Huai-long. Optimal Fire Distribution of a Rocket Launcher against Area Target [J]. Acta Armamentarii, 2017, 38(9): 1699-1704.
[7]	LEI Juan-mian, ZHANG Jia-wei, TAN Zhao-ming. Influence of Boattail on the Magnus Effect of Spinning Non-finned Projectile at Small Angles of Attack [J]. Acta Armamentarii, 2017, 38(9): 1705-1715.
[8]	LI Ze, YAN Xiao-peng, LI Ping, HAO Xin-hong, WANG Jian-tao. Jamming Mechanism of Frequency Sweep Jamming to FM Doppler Fuze [J]. Acta Armamentarii, 2017, 38(9): 1716-1722.
[9]	ZHANG Hao-wei, XIE Jun-wei, ZHANG Zhao-jian, ZONG Bin-feng, CHEN Tang-jun. Task Scheduling of Phased Array Radar Based on Hybrid Adaptive Genetic Algorithm [J]. Acta Armamentarii, 2017, 38(9): 1761-1770.
[10]	LI Mao， HOU Hai-liang， ZHU Xi， HUANG Xiao-ming， LI Dian， CHEN Chang-hai， HU Nian-ming. Influence of Structural Interspace on Anti-penetration Performance of Para-aramid Fiber-reinforced Composite Armor System [J]. Acta Armamentarii, 2017, 38(9): 1797-1805.
[11]	WANG Jian, HAN Yan, WANG Li-ming, ZHANG Pi-zhuang, CHEN Ping. Estimation Method for Instantaneous Frequency of Echo Signal of Projectile in Bore [J]. Acta Armamentarii, 2017, 38(9): 1806-1814.
[12]	LIU Hai-ou, ZHANG Wen-sheng, XU Yi, ZHAO Zi-ye. Load Spectrum Compiling for Transmission Shaft of Tracked Vehicle Based on Kernel Density Estimation [J]. Acta Armamentarii, 2017, 38(9): 1830-1838.
[13]	JIANG Miao-wen , YAN Jian-zhuo, CHEN Ji-min. 3D Printing of Military Helmet Liner Structure Based on Topology Optimization [J]. Acta Armamentarii, 2017, 38(9): 1845-1853.
[14]	ZHANG Lei, LI Shi-min, ZHU Gang. Study of Equipment Material Demand Prediction Method Based on Time-continuous Grey Markov Model [J]. Acta Armamentarii, 2017, 38(9): 1862-1866.
[15]	ZHANG Ya-zhou, LI Zhen-xiao, CHENG Nian-kai, TIAN Hui, LI Bao-ming. Research on a Triggered Vacuum Switch Pulsed Power Supply [J]. Acta Armamentarii, 2017, 38(8): 1469-1475.